Miguel Caballer, Germán Moltó, Amanda Calatrava, Ignacio Blanquer
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By supplementing TOSCA with additional types, the IM can also provision from FaaS platforms across the computing continuum by leveraging public cloud services such as AWS Lambda and on-premises serverless platforms, such as OSCAR. This allows event-driven data-processing applications across multiple computing platforms and architectures. The evolution of the Infrastructure Manager is described to accommodate the definition in TOSCA of complex applications that span across the computing continuum and their automated provisioning and configuration using Infrastructure as Code (IaC) approaches. Its effectiveness is assessed through a real use case involving a machine-learning classifier application for assisting in the early diagnosis of Rheumatic Heart Disease (RHD). The results show that the new developments enable the IM to efficiently deploy complete application architectures described in TOSCA across the computing continuum, from VMs to FaaS services.","PeriodicalId":54817,"journal":{"name":"Journal of Grid Computing","volume":"1 1","pages":"0"},"PeriodicalIF":3.6000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Infrastructure Manager: A TOSCA-Based Orchestrator for the Computing Continuum\",\"authors\":\"Miguel Caballer, Germán Moltó, Amanda Calatrava, Ignacio Blanquer\",\"doi\":\"10.1007/s10723-023-09686-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The edge-to-cloud continuum involves heterogeneous computing resources, including low-power physical devices, Virtual Machines (VMs) in cloud management platforms and serverless computing services based on the FaaS (Functions as a Service) model. This requires novel strategies to describe and efficiently deploy complex applications that execute across the computing continuum. To this end, this paper introduces the developments in the Infrastructure Manager (IM), an open-source TOSCA-based orchestrator to provision and configure virtualized computing resources from a wide range of cloud platforms. By supplementing TOSCA with additional types, the IM can also provision from FaaS platforms across the computing continuum by leveraging public cloud services such as AWS Lambda and on-premises serverless platforms, such as OSCAR. This allows event-driven data-processing applications across multiple computing platforms and architectures. The evolution of the Infrastructure Manager is described to accommodate the definition in TOSCA of complex applications that span across the computing continuum and their automated provisioning and configuration using Infrastructure as Code (IaC) approaches. Its effectiveness is assessed through a real use case involving a machine-learning classifier application for assisting in the early diagnosis of Rheumatic Heart Disease (RHD). 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Infrastructure Manager: A TOSCA-Based Orchestrator for the Computing Continuum
The edge-to-cloud continuum involves heterogeneous computing resources, including low-power physical devices, Virtual Machines (VMs) in cloud management platforms and serverless computing services based on the FaaS (Functions as a Service) model. This requires novel strategies to describe and efficiently deploy complex applications that execute across the computing continuum. To this end, this paper introduces the developments in the Infrastructure Manager (IM), an open-source TOSCA-based orchestrator to provision and configure virtualized computing resources from a wide range of cloud platforms. By supplementing TOSCA with additional types, the IM can also provision from FaaS platforms across the computing continuum by leveraging public cloud services such as AWS Lambda and on-premises serverless platforms, such as OSCAR. This allows event-driven data-processing applications across multiple computing platforms and architectures. The evolution of the Infrastructure Manager is described to accommodate the definition in TOSCA of complex applications that span across the computing continuum and their automated provisioning and configuration using Infrastructure as Code (IaC) approaches. Its effectiveness is assessed through a real use case involving a machine-learning classifier application for assisting in the early diagnosis of Rheumatic Heart Disease (RHD). The results show that the new developments enable the IM to efficiently deploy complete application architectures described in TOSCA across the computing continuum, from VMs to FaaS services.
期刊介绍:
Grid Computing is an emerging technology that enables large-scale resource sharing and coordinated problem solving within distributed, often loosely coordinated groups-what are sometimes termed "virtual organizations. By providing scalable, secure, high-performance mechanisms for discovering and negotiating access to remote resources, Grid technologies promise to make it possible for scientific collaborations to share resources on an unprecedented scale, and for geographically distributed groups to work together in ways that were previously impossible. Similar technologies are being adopted within industry, where they serve as important building blocks for emerging service provider infrastructures.
Even though the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines, including not only multiple domains of computer science (networking, middleware, programming, algorithms) but also application disciplines themselves, as well as such areas as sociology and economics, is needed to broaden the applicability and scope of the current body of knowledge.